scholarly journals Common Psychiatric Disorders and Caffeine Use, Tolerance, and Withdrawal: An Examination of Shared Genetic and Environmental Effects

2012 ◽  
Vol 15 (4) ◽  
pp. 473-482 ◽  
Author(s):  
Jocilyn E. Bergin ◽  
Kenneth S. Kendler
Keyword(s):  
Environmental Factors ◽  
Psychiatric Disorders ◽  
Genetic Correlations ◽  
Environmental Correlation ◽  
Caffeine Withdrawal ◽  
Decomposition Models ◽  
Correlation Parameters ◽  
Caffeine Dependence ◽  
Fitting Model ◽  
Shared Genetic

Background: Previous studies examined caffeine use and caffeine dependence and risk for the symptoms, or diagnosis, of psychiatric disorders. The current study aimed to determine if generalized anxiety disorder (GAD), panic disorder, phobias, major depressive disorder (MDD), anorexia nervosa (AN), or bulimia nervosa (BN) shared common genetic or environmental factors with caffeine use, caffeine tolerance, or caffeine withdrawal. Method: Using 2,270 women from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders, bivariate Cholesky decomposition models were used to determine if any of the psychiatric disorders shared genetic or environmental factors with caffeine use phenotypes. Results: GAD, phobias, and MDD shared genetic factors with caffeine use, with genetic correlations estimated to be 0.48, 0.25, and 0.38, respectively. Removal of the shared genetic and environmental parameter for phobias and caffeine use resulted in a significantly worse fitting model. MDD shared unique environmental factors (environmental correlation = 0.23) with caffeine tolerance; the genetic correlation between AN and caffeine tolerance and BN and caffeine tolerance were 0.64 and 0.49, respectively. Removal of the genetic and environmental correlation parameters resulted in significantly worse fitting models for GAD, phobias, MDD, AN, and BN, which suggested that there was significant shared liability between each of these phenotypes and caffeine tolerance. GAD had modest genetic correlations with caffeine tolerance, 0.24, and caffeine withdrawal, 0.35. Conclusions: There was suggestive evidence of shared genetic and environmental liability between psychiatric disorders and caffeine phenotypes. This might inform us about the etiology of the comorbidity between these phenotypes.

Shared genetic architecture across psychiatric disorders

2021 ◽  
pp. 1-7
Author(s):  
Andrew D. Grotzinger
Keyword(s):  
Risk Factors ◽  
Psychiatric Disorders ◽  
Genetic Correlations ◽  
Fine Grained ◽  
Level Data ◽  
Symptom Level ◽  
Genetic Level ◽  
Genetic Signal ◽  
Family Based ◽  
Shared Genetic

Abstract Psychiatric disorders overlap substantially at the genetic level, with family-based methods long pointing toward transdiagnostic risk pathways. Psychiatric genomics has progressed rapidly in the last decade, shedding light on the biological makeup of cross-disorder risk at multiple levels of analysis. Over a hundred genetic variants have been identified that affect multiple disorders, with many more to be uncovered as sample sizes continue to grow. Cross-disorder mechanistic studies build on these findings to cluster transdiagnostic variants into meaningful categories, including in what tissues or when in development these variants are expressed. At the upper-most level, methods have been developed to estimate the overall shared genetic signal across pairs of traits (i.e. single-nucleotide polymorphism-based genetic correlations) and subsequently model these relationships to identify overarching, genomic risk factors. These factors can subsequently be associated with external traits (e.g. functional imaging phenotypes) to begin to understand the makeup of these transdiagnostic risk factors. As psychiatric genomic efforts continue to expand, we can begin to gain even greater insight by including more fine-grained phenotypes (i.e. symptom-level data) and explicitly considering the environment. The culmination of these efforts will help to inform bottom-up revisions of our current nosology.

scholarly journals Testing structural models of psychopathology at the genomic level

2018 ◽  
Author(s):  
Irwin D. Waldman ◽  
Holly E. Poore ◽  
Justin M. Luningham ◽  
Jingjing Yang
Keyword(s):  
Bipolar Disorder ◽  
Eating Disorders ◽  
Psychiatric Disorders ◽  
Genetic Correlations ◽  
Structural Models ◽  
Higher Order ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Best Fitting ◽  
Fitting Model

Genome-wide association studies (GWAS) have revealed hundreds of genetic loci associated with the vulnerability to major psychiatric disorders, and post-GWAS analyses have shown substantial genetic correlations among these disorders. This evidence supports the existence of a higher-order structure of psychopathology at both the genetic and phenotypic levels. Despite recent efforts by collaborative consortia such as the Hierarchical Taxonomy of Psychopathology (HiTOP), this structure remains unclear. In this study, we tested multiple alternative structural models of psychopathology at the genomic level, using the genetic correlations among fourteen psychiatric disorders and related psychological traits estimated from GWAS summary statistics. The best-fitting model included four correlated higher-order factors – externalizing, internalizing, thought problems, and neurodevelopmental disorders – which showed distinct patterns of genetic correlations with external validity variables and accounted for substantial genetic variance in their constituent disorders. A bifactor model including a general factor of psychopathology as well as the four specific factors fit worse than the above model. Several model modifications were tested to explore the placement of some disorders – such as bipolar disorder, obsessive-compulsive disorder, and eating disorders – within the broader psychopathology structure. The best-fitting model indicated that eating disorders and obsessive-compulsive disorder, on the one hand, and bipolar disorder and schizophrenia, on the other, load together on the same thought problems factor. These findings provide support for several of the HiTOP higher-order dimensions and suggest a similar structure of psychopathology at the genomic and phenotypic levels.

scholarly journals Genetic and Environmental Basis in Phenotype Correlation Between Physical Function and Cognition in Aging Chinese Twins

2017 ◽  
Vol 20 (1) ◽  
pp. 60-65 ◽  
Author(s):  
Chunsheng Xu ◽  
Dongfeng Zhang ◽  
Xiaocao Tian ◽  
Yili Wu ◽  
Zengchang Pang ◽  
...  
Keyword(s):  
Visual Acuity ◽  
Cognitive Function ◽  
Environmental Factors ◽  
Physical Function ◽  
Handgrip Strength ◽  
Genetic Correlations ◽  
Bivariate Analysis ◽  
Environmental Correlation ◽  
Number Of Teeth ◽  
Near Visual Acuity

Although the correlation between cognition and physical function has been well studied in the general population, the genetic and environmental nature of the correlation has been rarely investigated. We conducted a classical twin analysis on cognitive and physical function, including forced expiratory volume in one second (FEV1), forced vital capacity (FVC), handgrip strength, five-times-sit-to-stand test (FTSST), near visual acuity, and number of teeth lost in 379 complete twin pairs. Bivariate twin models were fitted to estimate the genetic and environmental correlation between physical and cognitive function. Bivariate analysis showed mildly positively genetic correlations between cognition and FEV1, rG = 0.23 [95% CI: 0.03, 0.62], as well as FVC, rG = 0.35 [95% CI: 0.06, 1.00]. We found that FTSST and cognition presented very high common environmental correlation, rC = -1.00 [95% CI: -1.00, -0.57], and low but significant unique environmental correlation, rE = -0.11 [95% CI: -0.22, -0.01], all in the negative direction. Meanwhile, near visual acuity and cognition also showed unique environmental correlation, rE = 0.16 [95% CI: 0.03, 0.27]. We found no significantly genetic correlation for cognition with handgrip strength, FTSST, near visual acuity, and number of teeth lost. Cognitive function was genetically related to pulmonary function. The FTSST and cognition shared almost the same common environmental factors but only part of the unique environmental factors, both with negative correlation. In contrast, near visual acuity and cognition may positively share part of the unique environmental factors.

scholarly journals Characterising the shared genetic determinants of bipolar disorder, schizophrenia and risk-taking

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Guy Hindley ◽  
Shahram Bahrami ◽  
Nils Eiel Steen ◽  
Kevin S. O’Connell ◽  
Oleksandr Frei ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Psychiatric Disorders ◽  
Risk Taking ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association Studies ◽  
Increased Risk ◽  
Risky Behaviours ◽  
Shared Risk ◽  
Shared Genetic

AbstractIncreased risk-taking is a central component of bipolar disorder (BIP) and is implicated in schizophrenia (SCZ). Risky behaviours, including smoking and alcohol use, are overrepresented in both disorders and associated with poor health outcomes. Positive genetic correlations are reported but an improved understanding of the shared genetic architecture between risk phenotypes and psychiatric disorders may provide insights into underlying neurobiological mechanisms. We aimed to characterise the genetic overlap between risk phenotypes and SCZ, and BIP by estimating the total number of shared variants using the bivariate causal mixture model and identifying shared genomic loci using the conjunctional false discovery rate method. Summary statistics from genome wide association studies of SCZ, BIP, risk-taking and risky behaviours were acquired (n = 82,315–466,751). Genomic loci were functionally annotated using FUMA. Of 8.6–8.7 K variants predicted to influence BIP, 6.6 K and 7.4 K were predicted to influence risk-taking and risky behaviours, respectively. Similarly, of 10.2–10.3 K variants influencing SCZ, 9.6 and 8.8 K were predicted to influence risk-taking and risky behaviours, respectively. We identified 192 loci jointly associated with SCZ and risk phenotypes and 206 associated with BIP and risk phenotypes, of which 68 were common to both risk-taking and risky behaviours and 124 were novel to SCZ or BIP. Functional annotation implicated differential expression in multiple cortical and sub-cortical regions. In conclusion, we report extensive polygenic overlap between risk phenotypes and BIP and SCZ, identify specific loci contributing to this shared risk and highlight biologically plausible mechanisms that may underlie risk-taking in severe psychiatric disorders.

The Genetic and Environmental Structure of the Covariation Among the Symptoms of Insomnia, Fatigue, and Depression in Adult Females

2012 ◽  
Vol 15 (6) ◽  
pp. 720-726 ◽  
Author(s):  
Yoon-Mi Hur ◽  
Andrea Burri ◽  
Tim D. Spector
Keyword(s):  
Environmental Factors ◽  
Genetic Factors ◽  
Common Factor ◽  
Pathway Model ◽  
Symptoms Of Depression ◽  
The United Kingdom ◽  
Best Fitting ◽  
The Common ◽  
Fitting Model ◽  
Shared Genetic

Although the co-occurrence among symptoms of insomnia, fatigue, and depression has been frequently reported, the etiology of this co-occurrence remains poorly understood. A total of 3,758 adult female twins in the United Kingdom completed a mail-out survey including six questions concerning frequency and severity of symptoms of insomnia, fatigue, and depression. Correlations among the scores of the three symptoms ranged from 0.35 to 0.44. Among various multivariate models we tested, the common-pathway model explained the data best. In the best-fitting model, the common factor was explained approximately equally by genetic and unique environmental factors (49% and 51%, respectively). In addition to the common variance, there was a significant specific variance in each symptom, where unique environmental factors were much larger than genetic factors. These results imply that although there are shared genetic liabilities for the development of symptoms of depression, fatigue, and insomnia, it is environmental experiences that make etiological distinctions among three symptoms.

Insulin resistance: an atherothrombotic syndrome

2003 ◽  
Vol 89 (01) ◽  
pp. 161-168 ◽  
Author(s):  
Mark Freeman ◽  
Michael Mansfield ◽  
Jenny Barrett ◽  
Peter Grant
Keyword(s):  
Insulin Resistance ◽  
Environmental Factors ◽  
Genetic Correlation ◽  
Plasminogen Activator ◽  
Genetic Correlations ◽  
Fasting Insulin ◽  
Significant Genetic Correlation ◽  
Genetic And Environmental Factors ◽  
Pai 1 ◽  
Shared Genetic

SummaryThe insulin resistance syndrome (IRS) is a clustering of atherothrombotic traits associated with increased vascular risk. We investigated the degree to which the phenotypic correlations between these traits are due to shared genetic and environmental factors.A multivariate genetic analysis was performed in 537 adults from 89 healthy white north European families. All traits showed significant heritability. BMI had significant genetic correlations with fasting insulin, systolic blood pressure (sBP), plasminogen activator activator inhibitor-1 (PAI-1) and fibrinogen and triglyceride. Fasting insulin had a significant genetic correlation with fibrinogen and triglyceride and Factor VII (FVII). Significant genetic correlations were shown between triglyceride and PAI-1, fibrinogen and FVII. PAI-1 and tissue plasminogen activator (t-PA) showed significant genetic correlation with sBP and with each other. Pleiotropy was demonstrated between fibrino-gen and PAI-1, t-PA and FVII. Significant environmental correlations were also demonstrated.This study demonstrates pleiotropy between coagulation and fibrinolytic factors. Shared genetic and environmental factors influencing haemostatic, metabolic and anthropometric traits underlie the atherothrombotic nature of the IRS.

scholarly journals Dissecting the shared genetic architecture of suicide attempt, psychiatric disorders and known risk factors

2020 ◽  
Author(s):  
Niamh Mullins ◽  
Jooeun Kang ◽  
Adrian I Campos ◽  
Jonathan R I Coleman ◽  
Alexis C Edwards ◽  
...  
Keyword(s):  
Risk Factors ◽  
Suicide Attempt ◽  
Psychiatric Disorders ◽  
Risk Taking ◽  
Sleep Disturbances ◽  
Genetic Correlations ◽  
Genetic Etiology ◽  
Genome Wide ◽  
A Genome ◽  
Shared Genetic

AbstractSuicide is a leading cause of death worldwide and non-fatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both are known to have a substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium and conditioned the results on psychiatric disorders using GWAS summary statistics, to investigate their shared and divergent genetic architectures. Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, which remained associated after conditioning and has previously been implicated in risk-taking, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, lower socioeconomic status, pain, lower educational attainment, reproductive traits, risk-taking, sleep disturbances, and poorer overall general health. After conditioning, the genetic correlations between SA and psychiatric disorders decreased, whereas those with non-psychiatric traits remained largely unchanged. Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest the existence of a shared genetic etiology between SA and known risk factors that is not mediated by psychiatric disorders.

Shared genetic and environmental etiology between substance use disorders and suicidal behavior

2021 ◽  
pp. 1-9
Author(s):  
Alexis C. Edwards ◽  
Henrik Ohlsson ◽  
Séverine Lannoy ◽  
Mallory Stephenson ◽  
Casey Crump ◽  
...  
Keyword(s):  
Substance Use ◽  
Environmental Factors ◽  
Substance Use Disorders ◽  
Suicidal Behavior ◽  
Genetic Correlations ◽  
National Registry ◽  
Environmental Correlations ◽  
Drug Use Disorders ◽  
National Registry Data ◽  
Shared Genetic

Abstract Background Previous studies have demonstrated substantial associations between substance use disorders (SUD) and suicidal behavior. The current study empirically assesses the extent to which shared genetic and/or environmental factors contribute to associations between alcohol use disorders (AUD) or drug use disorders (DUD) and suicidal behavior, including attempts and death. Methods The authors used Swedish national registry data, including medical, pharmacy, criminal, and death registrations, for a large cohort of twins, full siblings, and half siblings (N = 1 314 990) born 1960–1980 and followed through 2017. They conducted twin-sibling modeling of suicide attempt (SA) or suicide death (SD) with AUD and DUD to estimate genetic and environmental correlations between outcomes. Analyses were stratified by sex. Results Genetic correlations between SA and SUD ranged from rA = 0.60–0.88; corresponding shared environmental correlations were rC = 0.42–0.89 but accounted for little overall variance; and unique environmental correlations were rE = 0.42–0.57. When replacing attempt with SD, genetic and shared environmental correlations with AUD and DUD were comparable (rA = 0.48–0.72, rC = 0.92–1.00), but were attenuated for unique environmental factors (rE = −0.01 to 0.31). Conclusions These findings indicate that shared genetic and unique environmental factors contribute to comorbidity of suicidal behavior and SUD, in conjunction with previously reported causal associations. Thus, each outcome should be considered an indicator of risk for the others. Opportunities for joint prevention and intervention, while limited by the polygenic nature of these outcomes, may be feasible considering moderate environmental correlations between SA and SUD.

A systematic analysis of genetically regulated differences in gene expression and the role of co-expression networks across 16 psychiatric disorders and substance use phenotypes

2021 ◽  
Author(s):  
Zachary F Gerring ◽  
Jackson G Thorp ◽  
Eric R Gamazon ◽  
Eske M Derks
Keyword(s):  
Gene Expression ◽  
Mental Health ◽  
Substance Use ◽  
Prefrontal Cortex ◽  
Psychiatric Disorders ◽  
Developmental Disorders ◽  
Association Studies ◽  
Genetic Correlations ◽  
Autism Spectrum ◽  
Genome Wide Association Studies

ABSTRACTGenome-wide association studies (GWASs) have identified thousands of risk loci for many psychiatric and substance use phenotypes, however the biological consequences of these loci remain largely unknown. We performed a transcriptome-wide association study of 10 psychiatric disorders and 6 substance use phenotypes (collectively termed “mental health phenotypes”) using expression quantitative trait loci data from 532 prefrontal cortex samples. We estimated the correlation due to predicted genetically regulated expression between pairs of mental health phenotypes, and compared the results with the genetic correlations. We identified 1,645 genes with at least one significant trait association, comprising 2,176 significant associations across the 16 mental health phenotypes of which 572 (26%) are novel. Overall, the transcriptomic correlations for phenotype pairs were significantly higher than the respective genetic correlations. For example, attention deficit hyperactivity disorder and autism spectrum disorder, both childhood developmental disorders, showed a much higher transcriptomic correlation (r=0.84) than genetic correlation (r=0.35). Finally, we tested the enrichment of phenotype-associated genes in gene co-expression networks built from prefrontal cortex. Phenotype-associated genes were enriched in multiple gene co-expression modules and the implicated modules contained genes involved in mRNA splicing and glutamatergic receptors, among others. Together, our results highlight the utility of gene expression data in the understanding of functional gene mechanisms underlying psychiatric disorders and substance use phenotypes.

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